Publications associées à Special issue on "Management of Future Motorway and Urban Traffic Systems"

Publications associées (15)

Data-driven control in atomic force microscopy using a genetic algorithm

Increasing the scanning speed in Atomic Force Microscopy (AFM) relies on improving the tracking performance in the vertical direction of motion. The lightly damped resonances of piezo-actuators utilized in AFM nano-positioning stages hinder the maximum ach ...

2025

On improving the efficiency of modifier adaptation via directional information

Dominique Bonvin

In real-time optimization, the solution quality depends on the model ability to predict the plant KarushKuhn-Tucker (KKT) conditions. In the case of non-parametric plant-model mismatch, one can add input-affine modifiers to the model cost and constraints a ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Sundar Subramaniam Ganesh

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

EPFL2022

Deep Q-learning agent for building earthquake resisting wall

Katrin Beyer, Qianqing Wang, Ketson Roberto Maximiano Dos Santos

The construction of dry-joint brick masonry that is subject to seismic loading can be modelled as a strategy problem wherein bricks must be laid to form a load resisting structure. To learn how to mount bricks while considering relevant engineering criteri ...

2022

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks

Volkan Cevher, Fabian Ricardo Latorre Gomez, Paul Thierry Yves Rolland, Shaul Nadav Hallak

We demonstrate two new important properties of the 1-path-norm of shallow neural networks. First, despite its non-smoothness and non-convexity it allows a closed form proximal operator which can be efficiently computed, allowing the use of stochastic proxi ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2020

A Time Splitting Based Real-Time Iteration Scheme for Nonlinear MPC

Colin Neil Jones, Yuning Jiang

This paper proposes a parallelizable real-time algorithm for model predictive control (MPC). In contrast to existing distributed and parallel optimization algorithms for linear MPC such as dual decomposition or the alternating direction method of multiplie ...

IEEE2019

Streaming Principal Component Analysis From Incomplete Data

Armin Eftekhari

Linear subspace models are pervasive in computational sciences and particularly used for large datasets which are often incomplete due to privacy issues or sampling constraints. Therefore, a critical problem is developing an efficient algorithm for detecti ...

Microtome Publishing2019

Optimal design methods applied to solar-assisted hydrothermal gasification plants

Alberto Mian

The gasification of highly watered waste residues may help to reduce fossil fuels consumption, as well as emissions, all the while improving efficiency. The integration of supercritical gasification with solar energy may improve the performances of both ne ...

EPFL2016

Optimal design of a squeeze film actuator for friction feedback

Yves Perriard, Yoan René Cyrille Civet, Christophe Winter

Sense of touch belongs to one of the five Human Senses. Whereas blind people largely use feeling in everyday life, sighted person mainly focus on hearing and vision. However, haptic interface started being introduced in customers applications, such as smar ...

IEEE Computer Society2013

Exploiting Local Quasiconvexity for Gradient Estimation in Modifier-Adaptation Schemes

Dominique Bonvin, Grégory François, Gene Bunin

A new approach for gradient estimation in the context of real-time optimization under uncertainty is proposed in this paper. While this estimation problem is often a difficult one, it is shown that it can be simplified significantly if an assumption on the ...

Ieee Computer Soc2012

Automatic Gait Generation in Modular Robots: to Oscillate or to Rotate? that is the question

Auke Ijspeert, Alexander Spröwitz, Soha Pouya, Jesse van den Kieboom

Modular robots offer the possibility to design robots with a high diversity of shapes and functionalities. This nice feature also brings an important challenge: namely how to design efficient locomotion gaits for arbitrary robot structures with many degree ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Locating leak detecting sensors in a water distribution network by solving prize-collecting Steiner arborescence problems

Thomas Liebling

We consider the problem of optimizing a novel acoustic leakage detection system for urban water distribution networks. The system is composed of a number of detectors and transponders to be placed in a choice of hydrants such as to provide a desired covera ...

Springer-Verlag2010

Integration of LCA in a thermo-economic model for multi-objective process optimization of SNG production from woody biomass

François Maréchal, Martin Gassner, Léda Gerber

This paper presents a methodology to integrate life cycle assessment (LCA) in models used to design energy conversion systems. It is illustrated by an application to a thermo-economic model for the multi-objective optimization of synthetic natural gas (SNG ...

2009

Reservoir Optimization in Recurrent Neural Networks using Kronecker Kernels

Martin Hasler, Mahdi Jalili, Ali Ajdari Rad

In this paper, using the mathematical properties of self-kronecker-production of small size random matrices, a simple but effective method is presented to optimize the reservoir of an echo state network given a certain task. The experimental results invest ...

IEEE2008

Model Parameterization Tailored to Real-Time Optimization

Dominique Bonvin, Benoît Chachuat

Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...

2008